Improvement of the agronomic characteristics of crop plants has been ongoing since the beginning of agriculture. Most of the land suitable for crop production is currently being used. As human populations continue to increase, improved crop varieties will be required to adequately provide our food and feed (Trewavas (2001) Plant Physiol. 125: 174-179). To avoid catastrophic famines and malnutrition, future crop cultivars will need to have improved yields with equivalent farm inputs. These cultivars will need to more effectively withstand adverse conditions such as drought, soil salinity or disease, which will be especially important as marginal lands are brought into cultivation. Finally, we will need cultivars with altered nutrient composition to enhance human and animal nutrition, and to enable more efficient food and feed processing. For all these traits, identification of the genes controlling phenotypic expression of traits of interest will be crucial in accelerating development of superior crop germplasm by conventional or transgenic means.
A number of highly-efficient approaches are available to assist identification of genes playing key roles in expression of agronomically-important traits. These include genetics, genomics, bioinformatics, and functional genomics. Genetics is the scientific study of the mechanisms of inheritance. By identifying mutations that alter the pathway or response of interest, classical (or forward) genetics can help to identify the genes involved in these pathways or responses. For example, a mutant with enhanced susceptibility to disease may identify an important component of the plant signal transduction pathway leading from pathogen recognition to disease resistance. Genetics is also the central component in improvement of germplasm by breeding. Through molecular and phenotypic analysis of genetic crosses, loci controlling traits of interest can be mapped and followed in subsequent generations. Knowledge of the genes underlying phenotypic variation between crop accessions can enable development of markers that greatly increase efficiency of the germplasm improvement process, as well as open avenues for discovery of additional superior alleles.
Genomics is the system-level study of an organism's genome, including genes and corresponding gene products—RNA and proteins. At a first level, genomic approaches have provided large datasets of sequence information from diverse plant species, including full-length and partial cDNA sequences, and the complete genomic sequence of a model plant species, Arabidopsis thaliana. Recently, the first draft sequence of a crop plant's genome, that of rice (Oryza sativa), has also become available. Availability of a whole genome sequence makes possible the development of tools for system-level study of other molecular complements, such as arrays and chips for use in determining the complement of expressed genes in an organism under specific conditions. Such data can be used as a first indication of the potential for certain genes to play key roles in expression of different plant phenotypes.
Bioinformatics approaches interface directly with first-level genomic datasets in allowing for processing to uncover sequences of interest by annotative or other means. Using, for example, similarity searches, alignments and phylogenetic analyses, bioinformatics can often identify homologs of a gene product of interest. Very similar homologs (eg. >−90% amino acid identity over the entire length of the protein) are very likely orthologs, i.e. share the same function in different organisms.
Functional genomics can be defined as the assignment of function to genes and their products. Functional genomics draws from genetics, genomics and bioinformatics to derive a path toward identifying genes important in a particular pathway or response of interest. Expression analysis, for example, uses high density DNA microarrays (often derived from genomic-scale organismal sequencing) to monitor the mRNA expression of thousands of genes in a single experiment. Experimental treatments can include those eliciting a response of interest, such as the disease resistance response in plants infected with a pathogen. To give additional examples of the use of microarrays, mRNA expression levels can be monitored in distinct tissues over a developmental time course, or in mutants affected in a response of interest. Proteomics can also help to assign function, by assaying the expression and post-translational modifications of hundreds of proteins in a single experiment.
Proteomics approaches are in many cases analogous to the approaches taken for monitoring mRNA expression in microarray experiments. Protein-protein interactions can also help to assign proteins to a given pathway or response, by identifying proteins that interact with known components of the pathway or response. For functional genomics, protein-protein interactions are often studied using large-scale yeast two-hybrid assays. Another approach to assigning gene function is to express the corresponding protein in a heterologous host, for example the bacterium Escherichia coli, followed by purification and enzymatic assays.
Demonstration of the ability of a gene-of-interest to control a given trait may be derived, for example, from experimental testing in plant species of interest. The generation and analysis of plants transgenic for a gene of interest can be used for plant functional genomics, with several advantages. The gene can often be both overexpressed and underexpressed (“knocked out”), thereby increasing the chances of observing a phenotype linking the gene to a pathway or response of interest. Two aspects of transgenic functional genomics help lend a high level of confidence to functional assignment by this approach. First, phenotypic observations are carried out in the context of the living plant. Second, the range of phenotypes observed can be checked and correlated with observed expression levels of the introduced transgene. Transgenic functional genomics is especially valuable in improved cultivar development. Only genes that function in a pathway or response of interest, and that in addition are able to confer a desired trait-based phenotype, are promoted as candidate genes for crop improvement efforts. In some cases, transgenic lines developed for functional genomics studies can be directly utilized in initial stages of product development.
Another approach towards plant functional genomics involves first identifying plant lines with mutations in specific genes of interest, followed by phenotypic evaluation of the consequences of such gene knockouts on the trait understudy. Such an approach reveals genes essential for expression of specific traits.
Genes identified through functional genomics can be directly employed in efforts towards germplasm improvement by transgenic means, as described above, or used to develop markers for identification of tracking of alleles-of-interest in mapping and breeding populations. Knowledge of such genes may also enable construction of superior alleles non-existent in nature, by any of a number of molecular methods.
Rapid increases in yield over the last 80 years in row crops have been due in roughly equal measure to improved genetics and improved agronomic practices. In particular, in a crop like maize, the combination of high yielding hybrids and the use of large amounts of nitrogen fertilizer have under ideal conditions allowed for yields of greater than 440 bu/acre. However, the use of large amounts of nitrogen fertilizer has negative side-effects primarily around increasing cost of this input to the farmer and cost to the environment since nitrate pollution is a major problem in many agricultural areas contributing significantly to the degradation of both fresh water and marine environments. Developing crop genetics that use nitrogen more efficiently through an understanding of the role of genotype on nitrogen use would be highly advantageous in reducing producer input costs as well as environmental load. This is particularly important for a crop like corn which is grown using a high level of nitrogen fertilizer.
Nitrogen use efficiency can be defined in several ways, although the simplest is yield/N supplied. There are two stages in this process: first, the amount of available nitrogen that is taken up, stored and assimilated into amino acids and other important nitrogenous compounds; second, the proportion of nitrogen that is partitioned to the seed, resulting in final yield. A variety of field studies have been performed on various agriculturally-important crops to study this problem (Lawlor D W et al 2001 in Lea P J, Morot-Gaudry J F, eds. Plant Nitrogen. Berlin: Springer-Verlag 343-367; Lafifte H R and Edmeades G O 1994 Field Crops Res 39, 15-25; Lawlor D W 2002 J Exp Bot. 53, 773-87; Moll R H et al 1982 Agron J 74, 562-564). These experiments have demonstrated that there is a genetic component to nitrogen use efficiency, but have not proved satisfactory in determining which genes are important for this process. In addition, corn breeders have generally not targeted the maintenance of yield under limiting nitrogen fertilizer. These types of field experiments on nitrogen use are difficult for a variety of reasons including a lack of uniformity of accessible nitrogen in a test field or between field sites under any treatment regime and the interplay of other environmental factors that make experiments difficult to interpret.
Therefore, although there is experimental evidence for genetic variation for this trait, it is difficult to make any conclusions from these experiments on what causes this variation. It should be feasible and is certainly important to develop methods to study this trait under field conditions in crop plants. However, significant progress toward identifying, understanding and manipulating important traits can be made through the use of a model system like Arabidopsis. At the very least, these experiments will give important clues about potential target genes to evaluate in important field crops. In addition, there are also considerable genetic and genomic resources available to study rice and this species will also be used for some of the proposed experiments as a species more similar to corn than is Arabidopsis. 
Nitrate is the major form of available nitrogen in the field and there is an extensive body of literature on genes involved in nitrate uptake and reduction (Forde B G 2000 Biochimica et Biophysica Acta 1465, 219-235; Howift S M and Udvardi M K 2000 Biochimica et Biophysica Acta 1465, 152-170; Stitt M et al 2002 J Exp Bot. 53, 959-70) as well as on genes involved in other aspects of nitrogen metabolism (Lea P J, Morot-Gaudry J F, eds. 2001 Plant Nitrogen. Berlin; Springer-Verlag; Morot-Gaudry J F 2001 Nitrogen assimilation by plants Science Publishers Inc. NH, US). Also, it is clear that the availability of carbon metabolites is crucial for the efficient use of field nitrate and there is good experimental evidence for a linkage between carbon and nitrogen metabolism (Coruzzi G M and Zhou L 2001 Curr Opin Plant Biol. 4, 247-53). In addition, some experiments suggest that GS and GOGAT are involved in remobilizing N from senescing organs to the sink organ (Brouquisse R et al 2001 in Lea P J, Morot-Gaudry J F, eds. Plant Nitrogen. Berlin: Springer-Verlag 275-293; Yamaya T et al 2002 J Exp Bot. 53, 917-925). However, most aspects of the regulation of these genes are still unclear and there is still no notion of how this regulation affects nitrogen use efficiency.
Plants can sense levels of carbon and nitrogen metabolites and accordingly adjust growth and development. The perception mechanisms are complex regulatory networks that control gene expression to accommodate constant changes of nutrient-dependent cellular activities. Possession of a sugar-sensing mechanism enables plants to turn off photosynthesis when C-skeletons are abundant. The N-sensing mechanism enables plants to turn off nitrate uptake and reduction when levels of reduced or organic N are high (Coruzzi, G. M. & Zhou, L. (2001) Curr Opin Plant Biol. 4, 247-53).
Multiple sugar signal transduction pathways exist in plants. Glucose has emerged as a key regulator of many vital processes in photosynthetic plants such as in photosynthesis and in carbon and nitrogen metabolism (Roland, F., Moore, B. & Sheen, J. (2002) Plant Cell S185-S205). Hexokinases (HXK) are an important control point for glucose metabolism. They not only catalyze the phosphorylation of glucose but also function as a glucose sensor to interrelate nutrient, light and hormone signaling networks for controlling growth and development in response to the changing environment (Jang, J., Leon, P; Zhou, L. & Sheen, J. (1997) Plant Cell 9, 5-19; Dai, N., Schaffer, A., Petreikov, M., Shahak, Y., Giller, Y., Ratner, K., Levine, A. & Granot, D. (1999) Plant Cell 11, 1253-1266; Moore, B., Zhou, L., Rolland, F., Hall, Q., Cheng, W., Liu, Y., Hwang, I., Jones, T. & Sheen, J. (2003) Science 300, 332-336). In other organisms it has been shown that hexose transport molecules also serve as sugar sensors.
Multiple N signals and sensing pathways exist as well in plants. Plants have mechanisms to sense nitrate, the major form of nitrogen fertilizer, as a signal for inorganic N status as well as to sense metabolites derived from nitrate as signals for reduced or organic N status. Nitrate reductase (NR) and nitrite reductase (NiR) are the first two enzymes in the nitrate reduction process and their expression can be stimulated by the presence of nitrate and modulated by other physiological factors including some nitrogenous compounds, sucrose, light and hormone (Forde, B. G. (2000) Biochimica et Biophysica Acta 1465, 219-235; Howitt, S. M. & Udvardi, M. K. (2000) Biochimica et Biophysica Acta 1465, 152-170; Stift, M., Müller, M., Maft, M., Gibon, Y., Carilio, P., Morcuende, R., Scheible, W. & Krapp, A. (2002) J Exp Bot. 53, 959-970; Lea, P. J. & Morot-Gaudry, J. F. eds. 2001 Plant Nitrogen. Berlin: Springer-Verlag; Morot-Gaudry J F 2001 Nitrogen assimilation by plants Science Publishers Inc. NH, US).
It is clear that carbon and nitrogen metabolism is closely linked and tightly regulated (Coruzzi, G. & Bush, D. R. (2001) Plant Physiol 125, 61-64). The availability of carbon metabolites is crucial for efficient nitrate utilization and the nitrogen status is very sensitive to photosynthesis. Despite increased knowledge of structural genes involved in carbon and nitrogen metabolism, trans-acting factors involved in transcriptional regulation of C/N gene expression have not been characterized.
GATA transcription factors are a group of transcriptional regulators broadly distributed in eukaryotes. The GATA DNA binding domain normally recognizes the consensus sequence WGATAR (W=T or A; R=G or A) (Lowry, J. & Atchley, W. (2000) J Mol Evol 50, 103-115). GATA motifs have been identified in the regulatory regions of many light responsive genes (Arguello-Astorga, G & Herrera-Estrella, L. (1998) Annu Rev Plant Physiol Plant Mol Biol 49, 525-555), including many genes involved in or relating to photosynthesis such as the RBCS, CAB (chlorophyll A/B binding protein) and GAP (glyceraldehyde-3-phosphate dehydrogenase) (Terzaghi, W. B. & Cashmore, A. R. (1995) Annu Rev Plant Physiol Plant Mol Biol 46, 445-474; Koch, K. E. (1996) Carbohydrate-modulated gene expression in plants. Annu Rev Plant Physiol Plant Mol Biol 47, 509-540; Jeong, M. J. & Shih, M. C. (2003) Biochem Biophys Res Commun 300, 555-562) as well as genes involved in nitrate assimilation such as nitrate reductase, nitrite reductase, and Gln synthetase (Jarai, G., Truong, H., Daniel-Vedele, F. & Marzluf, G. (1992) Curr Genet. 21, 37-41; Rastogi, R., Bate, N., Sivasankar, S & Rothstein, S. (1997) Plant Mol Biol. 34, 465-76; Oliveira, I. C. & Coruzzi, G. M. (1999) Plant Physiol 121, 301-309). Some known trans-acting regulatory proteins that globally regulate genes in N metabolism are GATA transcription factor genes. In yeast, four global nitrogen regulatory factors GLN3, NIL1, NIL2 and DAL80 are DNA-binding proteins that contain a single GATA zinc finger, recognizing the consensus motif GATA (Hofman-Bang, J. (1999) Mol Biotech 12, 35-73). In fungi, Neurospora crassa NIT2 (Tao Y and Marzluf G A 1999 Curr Genet. 36, 153-158) and Aspergillus nidulans AREA (Caddick M X Arst H N Jr Taylor L H Johnson R I Brownlee A G 1986 Cloning of the regulatory gene areA mediating nitrogen metabolite repression in Aspergillus nidulans. EMBO J 5, 1087-1090) are GATA transcription factor genes.
In plants, the in vivo function of GATA factors remains very poorly defined, with the Arabidopsis genome having 30 GATA members (Riechmann, J. L., Heard, J., Martin, G., Reuber, L., Jiang, C., Keddie, J., Adam, L., Pineda, O., Ratcliffe, O. J., Samaha, R. R., Creelman, R., Pilgrim, M., Broun, P., Zhang, J. Z., Ghandehari, D., Sherman, B. K. & Yu, G. (2000) Science 290, 2105-2110; Reyes, J. C., Muro-Pastor, M. I. & Florencio, F. J. (2004) Plant Physiol. 134, 1718-1732).